Hierarchical Iterative Eigendecomposition for Motion Segmentation
نویسندگان
چکیده
This paper applies a new clustering approach for identifying and segmenting motion in image sequences. We estimate a matrix whose entries represent similarity probabilities between local motion estimates. We adopt a two step iterative algorithm which consists of a variant of the expectationmaximization algorithm for segmenting regions with similar motion. The proposed algorithm updates cluster memberships in one step while it maximizes the expected loglikelihood in the second step. The performance of the algorithm is improved greatly by the use of modal sharpening.
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تاریخ انتشار 2001